Method, apparatus, and computer-readable storage medium for grouping social network nodes

ABSTRACT

According to an embodiment, a candidate node having a potential association relationship with a target node, an association node having an association relationship with the target node, and a grouping identifier of the association node are obtained. A relevance degree between the association node and the target node and a relevance degree between the candidate node and the target node within each grouping identifier are obtained. Based on the relevance degrees, the association node and the candidate node in each grouping identifier are combined for outputting.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a U.S. National Phase application under 35 U.S.C. §371 of International Application No. PCT/CN2013/071038, filed Jan. 28,2013, entitled “Method, Apparatus, and Computer-Readable Storage Mediumfor Grouping Social Network Nodes”, the entire disclosure of which isincorporated herein by reference.

FIELD OF THE INVENTION

Embodiments of the present disclosure relate to Internet technology, andmore particularly, to a method, apparatus, and computer-readable storagemedium for grouping social network nodes.

BACKGROUND OF THE INVENTION

Social networks are booming with the development of the Internettechnology. The social network includes websites and products that mayprovide connections between people, including but not limited to instantmessaging products, social networking websites, chat rooms, BBS, virtualcommunities, online games, and so on. In the social network, a user mayserve as a node, and there may be a direct buddy relationship or anindirect relationship between users. In other words, there may be anassociation relationship between nodes, or there may be a potentialassociation relationship between the nodes. The social network mayprovide the potential association relationship between the nodes, whichmay facilitate the development of a relationship chain between thenodes, so that the potential association relationship may be transformedinto the association relationship. In the social network, a user may beregarded as a target node. A node having the association relationshipwith the target node may be regarded as an association node, and a nodehaving the potential association relationship with the target node maybe regarded as a candidate node. For example, the association node is abuddy of the user and the candidate node is a potential buddy of theuser. In this case, the potential buddy may indicate a user who maybecome a buddy of the user. By this manner, the potential buddy may berecommended to the user, so that an online relationship chain of theuser may be developed.

In a traditional social network, the “association node and the candidatenode” may be divided into two blocks for presenting to the target node.The target node only interacts data information with the associationnode, in which there is the association relationship between the targetnode and the association node. When the target node wants to interactwith the candidate node having the potential association relationshipwith the target node, the candidate node may be required to betransformed into the association node. The target node may search ablock where the candidate node locates for the data of the candidatenode, which is inconvenient and difficult for the target node to quicklyexpand the relationship chain of the target node.

SUMMARY OF THE INVENTION

Embodiments of the present disclosure provide a method for groupingsocial network nodes. The method includes:

-   -   obtaining a candidate node having a potential association        relationship with a target node, an association node having an        association relationship with the target node, and a grouping        identifier of the association node;    -   obtaining a relevance degree between the association node and        the target node and a relevance degree between the candidate        node and the target node within each grouping identifier; and    -   combining, based on the relevance degrees, the association node        and the candidate node in each grouping identifier and        outputting the association node and the candidate node.

Embodiments of the present disclosure further provide an apparatus forgrouping social network nodes. The apparatus includes:

-   -   an extracting module, to obtain a candidate node having a        potential association relationship with a target node, an        association node having an association relationship with the        target node, and a grouping identifier of the association node;    -   a processing module, to obtain a relevance degree between the        association node and the target node and a relevance degree        between the candidate node and the target node within each        grouping identifier; and    -   an outputting module, to combine, based on the relevance        degrees, the association node and the candidate node in each        grouping identifier and output the association node and the        candidate node.

Embodiments of the present disclosure further provide a non-transitorycomputer-readable storage medium. The non-transitory computer-readablestorage medium is encoded with a plurality of instructions that whenexecuted by one or more computers cause the one or more computers toperform operations comprising:

-   -   obtaining a candidate node having a potential association        relationship with a target node, an association node having an        association relationship with the target node, and a grouping        identifier of the association node;    -   obtaining a relevance degree between the association node and        the target node and a relevance degree between the candidate        node and the target node within each grouping identifier; and    -   combining, based on the relevance degrees, the association node        and the candidate node in each grouping identifier and        outputting the association node and the candidate node.

According to various embodiments of the present disclosure, in themethod, apparatus, and computer-readable storage medium as describedabove, the candidate node, the association node, and the groupingidentifier of the association node are obtained. The relevance degreebetween the candidate node and the target node and the relevance degreebetween the association node within each grouping identifier and thetarget node are obtained. Based on the relevance degrees, theassociation node and the candidate node in each grouping identifier arecombined for outputting. The method, apparatus, and computer-readablestorage medium described in the various embodiments of the presentdisclosure can facilitate the operation, reduce the operationsimplemented by the user for adding the candidate node, and improve theresponse efficiency of the system.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a flowchart illustrating a method for grouping social networknodes, according to an embodiment of the present disclosure.

FIG. 2 is a flowchart illustrating a process at block S20, according toan embodiment of the present disclosure.

FIG. 3 is a schematic diagram illustrating a node relationship,according to an embodiment of the present disclosure.

FIG. 4 is a schematic diagram illustrating the presenting of associationnodes and candidate nodes, according to an embodiment of the presentdisclosure.

FIG. 5 is a schematic diagram illustrating the presenting of buddies andpotential buddies, according to an embodiment of the present disclosure.

FIG. 6 is a schematic diagram illustrating a structure of an apparatusfor grouping social network nodes, according to an embodiment of thepresent disclosure.

FIG. 7 is a schematic diagram illustrating a structure of a processingmodule, according to an embodiment of the present disclosure.

FIG. 8 is a schematic diagram illustrating a structure of an outputtingmodule, according to an embodiment of the present disclosure.

FIG. 9 is a schematic diagram illustrating a structure of an apparatusfor grouping social network nodes, according to another embodiment ofthe present disclosure.

DETAILED DESCRIPTION OF THE INVENTION

Hereinafter, the present disclosure will be described in further detailwith reference to the accompanying drawings and exemplary embodiments.

As shown in FIG. 1, according to an embodiment of the presentdisclosure, a method for grouping nodes in a social network may includefollowing operations.

In block S10, a candidate node having a potential associationrelationship with a target node, an association node having anassociation relationship with the target node, and a grouping identifierof the association node may be obtained.

In this case, a user in the social network may be selected as the targetnode. A user having a buddy relationship with the user may be regardedas the association node, i.e., a node having the associationrelationship with the target node may be regarded as the associationnode. A user having a potential buddy relationship with the user may beregarded as the candidate node, i.e., a node having the potentialassociation relationship with the target node may be regarded as thecandidate node. According to an embodiment of the present disclosure,the potential association relationship may be defined to mean that theremay be a possibility for the candidate node to have the associationrelationship with the target node. The candidate node having thepotential association relationship with the target node may be obtainedin advance. The candidate node may be placed in a candidate node list. Acandidate node associated with the target node may be obtained from thecandidate node list. According to embodiments of the present disclosure,there may be various ways for obtaining the candidate node from thecandidate node list. For example, a matching weight of attributeinformation of the target node may be preconfigured. Attributeinformation of nodes which do not have the association relationship withthe target node may be compared with the attribute information of thetarget node, so as to obtain weights of the nodes which do not have theassociation relationship with the target node. When a weight of a nodethat does not have the association relationship with the target node isgreater than a threshold, the node may be regarded as the candidatenode. The attribute information of a node may include true informationsuch as gender, age, constellation, a blood type, a graduate school, amajor, a graduation date, a native place, a location where the nodelocates, a job, hobbies, and so forth. When the social network is avirtual social network, the attribute information of the node mayfurther include an area where the node locates in the virtual world,attributes of a virtual character, a level of the virtual character, andetc.

According to an embodiment of the present disclosure, the groupingidentifier may include but not be limited to junior high schoolclassmate, senior high school classmate, college schoolmate, colleague,family, and etc. According to another embodiment of the presentdisclosure, the grouping identifier may be a group number (ID), such asgroup 001, group 002.

In block S20, a relevance degree between the association node and thetarget node and a relevance degree between the candidate node and thetarget node within each grouping identifier may be obtained.

In this case, according to an embodiment of the present disclosure, therelevance degree between the candidate node and the target node may beobtained according to the grouping identifier, and the relevance degreebetween the association node in each grouping identifier and the targetnode may be obtained. The relevance degree may refer to a matchingdegree between the attribute information of the target node and theattribute information of the candidate node, or between the attributeinformation of the target node and the attribute information of theassociation node. According to an embodiment of the present disclosure,the relevance degree may be defined to mean a similarity degree of theattribute information between users.

According to an embodiment of the present disclosure, as shown in FIG.2, the operations in block S20 may be implemented as follows.

In block S210, a condition for determining there is the associationrelationship between a node and an intra-group node may bepreconfigured.

In this case, the target node, the association node, and the candidatenode may be regarded as the node. Association relationships between thenode and each intra-group node may be counted. According to anembodiment of the present disclosure, there may be two ways forobtaining the relevance degree of the node. According to a first way,when the intra-group nodes include the association nodes, the relevancedegree of the node may be obtained by counting the number of intra-groupassociation nodes having the association relationship with the node.According to a second way, when the intra-group nodes include theassociation nodes and the target node, the relevance degree of the nodemay be obtained by counting the number of the intra-group associationnodes plus the target node, in which the intra-group association nodeshave the association relationship with the node.

According to an embodiment of the present disclosure, the preconfiguredcondition for determining there is the association relationship betweenthe node and the intra-group node may include at least one of thefollowing conditions.

A first condition may be that the node itself is the intra-group node.

For example, when group 001 of target node A includes association nodeB, then association node B is an intra-group association node. Whenassociation node B is regarded as the node and the number of nodes ingroup 001 that may have the association relationship with associationnode B is counted, association node B itself may be counted.

A second condition may be that the node has the association relationshipwith the intra-group node.

For example, group 001 of target node A includes association node B,association node C, and association node D, in which association node Bhas the association relationship with association node C. Whenassociation node B is regarded as the node and the number of nodes ingroup 001 that may have the association relationship with associationnode B is counted, association node C meets the second condition and isregarded as a node in group 001 that has the association relationshipwith association node B.

A third condition may be that when the node has the associationrelationship with a predetermined number of candidate nodes and thepredetermined number of candidate nodes have the associationrelationship with the intra-group node, the node may have theassociation relationship with the intra-group node.

In this case, an intra-group association node may be a buddy of theuser, and a candidate node may likely to be a buddy of the user. Forexample, group 001 of target node A may include association node B,association node C, and association node D. Candidate nodes outside thegroup may include nodes E, F, G, and H. The predetermined number may bethree. Assuming candidate node E has the association relationship withcandidate nodes F, G and H, and association node B also has theassociation relationship with the candidate nodes F, G, and H, whencandidate node E is regarded as the node and the number of nodes ingroup 001 that may have the association relationship with candidate nodeE is counted, association node B meets the third condition and isregarded as a node in group 001 that has the association relationshipwith candidate node E.

In block S220, based on the condition, the number of intra-group nodeshaving the association relationship with each node may be obtained.

For example, based on the condition, the number of nodes in group 001that may have the association relationship with association node B maybe counted, and the number of nodes in group 002 that may have theassociation relationship with association node B may be counted.

In block S230, a ratio of the number of the intra-group nodes having theassociation relationship with each node to the number of the intra-groupnodes may be configured as the relevance degree between each node andthe target node.

Hereinafter, the process for obtaining the relevance degree between eachnode and the target node may be described in further detail. As shown inFIG. 3, assuming there is a group G1 that has the associationrelationship with a target node A, in which group G1 includes sevenassociation nodes including B1 to B7 and four candidate nodes includingA1 to A4. The predetermined number may be three. According to anembodiment of the present disclosure, assuming the intra-group nodesinclude the association nodes, the nodes in G1 that may have theassociation relationship with A1 may include B1 (which meets the secondcondition), B3 (which meets the second condition), B6 (which meets thesecond condition and the third condition), and B5 (which meets the thirdcondition), as such, the relevance degree of A1 may be 4/7. The nodes inG1 that may have the association relationship with B5 may include B5(which meets the first condition), B1 (which meets the secondcondition), B2 (which meets the second condition), B4 (which meets thesecond condition), B7 (which meets the second condition), and B6 (whichmeets the third condition), as such, the relevance degree of B5 may be6/7. When the relevance degree is obtained in accordance with thesituation that the intra-group nodes include the association nodes, itmay be beneficial for obtaining the relevance degree of the candidatenode that is greater than the relevance degree of the association node.As such, when the nodes are sorted in a descending order of therelevance degrees, more candidate nodes may be arranged ahead, which mayfacilitate operations to the candidate nodes.

According to another embodiment of the present disclosure, assuming theintra-group nodes include the association nodes and the target node,i.e., the target node may be regarded as a statistic node for obtainingthe relevance degree, as such, the nodes in the group G1 having theassociation relationship with A1 may include B1 (which meets the secondcondition), B3 (which meets the second condition), B6 (which meets thesecond condition and the third condition), and B5 (which meets the thirdcondition), so that the relevance degree of A1 may be 4/8. The nodes inthe group G1 having the association relationship with B5 may include B5(which meets the first condition), B1 (which meets the secondcondition), B2 (which meets the second condition), B4 (which meets thesecond condition), B7 (which meets the second condition), B6 (whichmeets the third condition), and the target node A, so that the relevancedegree of B5 may be 7/8.

In block S30, based on the relevance degrees, the association node andcandidate node in each grouping identifier may be combined foroutputting.

According to an embodiment of the present disclosure, the associationnode and the candidate node in each group may be combineddiscretionarily and then output.

According to an embodiment of the present disclosure, the operations inblock S30 may be implemented as follows. The association node and thecandidate node in each grouping identifier may be sorted based on therelevancy degrees. The sorted association node and candidate node may bepresented according to the grouping identifier.

Specifically, in each grouping identifier, the association node and thecandidate node in the group may be sorted based on the relevancedegrees. As shown in FIG. 3, in the grouping identifier G1, therelevance degrees of A1, A2, A3, and A4 respectively are 4/7, 2/7, 2/7,and 2/7, and the relevance degrees of B1, B2, B3, B4, B5, B6, and B7respectively are 5/7, 5/7, 4/7, 4/7, 6/7, 6/7, and 3/7. When these nodesare sorted in a descending order of the relevance degrees, the nodes maybe presented as B5, B6, B1, B2 B3, B4, A1, B7, A2, A3, and A4. Accordingto another embodiment of the present disclosure, the nodes may be sortedin an ascending order of the relevancy degrees.

After each group is sorted, the sorted association node and candidatenode may be presented according to the grouping identifier. As shown inFIG. 4, there are three option controls on a display interface, whichmay display the association node, or display the candidate node, ordisplay all of the nodes. An association node list includes group 1 andgroup 2. Group 1 includes association node 1, candidate node 1,association node 2, candidate node 2, association node 3, candidate node3, and candidate node 4. Group 2 includes association node 4,association node 5, candidate node 5, and association node 6. Accordingto an embodiment of the present disclosure, when the association nodeand the candidate node are presented, the association node and thecandidate node may be marked with different labels for distinguishingpurpose. As shown in FIG. 4, a solid-line smiley may be marked before anassociation node and a dotted-line smiley may be marked before acandidate node. According to embodiments of the present disclosure, thelabel may be configured by either the user or the system.

According to an embodiment of the present disclosure, when the relevancydegree of the candidate node in the grouping identifier is 0, thecandidate node may be hidden in the grouping identifier, alternatively,the candidate node may not be added to the grouping identifier. Forexample, when group 001 is processed, a relevancy degree betweencandidate node H and the target node is 0, so that candidate node H maynot be added to group 001. When group 002 is processed, the relevancydegree between candidate node H and the target node is not equal to 0,so that candidate node H may be added to group 002.

According to another embodiment of the present disclosure, in the methodfor grouping the social network nodes, the operation of sorting, basedon the relevancy degrees, the association node and the candidate node ineach grouping identifier may include sorting the association node andthe candidate node in each grouping identifier in the descending orderof the relevancy degrees.

According to an embodiment of the present disclosure, the operation ofpresenting the sorted association node and candidate node according tothe grouping identifier may include presenting, within each groupingidentifier, a predetermined number or a user-determined number ofsorting results with high relevancy degrees. For example, referring toFIG. 3 again, in group G1, the relevance degrees of A1, A2, A3, and A4respectively are 4/7, 2/7, 2/7, and 2/7, and the relevance degrees ofB1, B2, B3, B4, B5, B6, and B7 respectively are 5/7, 5/7, 4/7, 4/7, 6/7,6/7, and 3/7. When these nodes are sorted in the descending order of therelevance degrees, the nodes may be presented as B5, B6, B1, B2, B3, B4,A1, B7, A2, A3, and A4. When the predetermined number is 7, B5, B6, B1,B2, B3, B4, and A1 may be presented. When the user-determined number is6, B5, B6, B1, B2, B3, and B4 may be presented. In addition, theuser-determined number may be adjusted by the user at any time.

According to another embodiment of the present disclosure, in the methodfor grouping the social network nodes, after obtaining the relevancydegree between the association node and the target node and therelevancy degree between the candidate node and the target node in eachgroup, the method further include configuring a relevancy threshold andhiding a candidate node of which a relevancy degree is less than therelevancy threshold. Thereafter, in each group in which the candidatenode of which the relevancy degree is less than the relevancy thresholdis hidden, the association node and the candidate node are sortedaccording to the relevancy degrees, and the sorted association node andcandidate node are presented according to the grouping identifier.According to an embodiment of the present disclosure, the relevancythreshold may be configured by either the user or the system accordingto requirements. When the relevancy threshold is preconfigured, it maybe determined whether a relevancy degree of a candidate node is lessthan the relevancy threshold. In response to determining that therelevancy degree of the candidate node is less than the relevancythreshold, the candidate node may be hidden. In response to determiningthat the relevancy degree of the candidate node is equal to or greaterthan the relevancy threshold, the candidate node may be presented. In anembodiment, all of association nodes of the target node may be presentedto the user. In addition, the user may configure the relevancy thresholdat any time according to the requirements. For example, a slider controlmay be configured on an interface, and the relevancy threshold may beadjusted through sliding the slider control. According to anotherembodiment, after the sorted association node and candidate node arepresented, the candidate node of which the relevancy degree is less thanthe relevancy threshold may be hidden based on the relevancy thresholdconfigured by the user.

According to another embodiment of the present disclosure, in the methodfor grouping the social network nodes, within each group in which thecandidate node of which the relevancy degree is less than the relevancythreshold is hidden, the association node and the candidate node may besorted in the descending order of the relevancy degrees, and thepredetermined number or the user-determined number of sorting resultswith high relevancy degrees may be presented within each groupingidentifier.

According to another embodiment of the present disclosure, the methodfor grouping the social network nodes may further include obtaining adisplay setting selected by the user, and presenting the sortedassociation node and candidate node according to the display setting andthe grouping identifier. Specifically, the display setting selected bythe user may include any one of presenting the association node,presenting the candidate node, and presenting all of the nodes. Thepresenting may be performed according to a corresponding displaysetting. For example, referring to FIG. 3 again, when the displaysetting is configured to present the association node, the associationnodes B1 to B7 may be presented. When the display setting is configuredto present the candidate node, the candidate nodes A1 to A4 may bepresented. When the display setting is configured to present all of thenodes, all of the sorted association node and candidate node may bepresented.

According an embodiment of the present disclosure, when the method forgrouping the social network nodes is applied to the grouping of buddiesand potential buddies of the user, the method may include followingoperations.

At step (a), a potential buddy of the user, a buddy grouping identifier,and an intra-group buddy of the user may be obtained.

In this case, the potential buddy of the user may refer to a person whomthe user may know or a person who may become a buddy of the user. Thepotential buddy may be a candidate node. The buddy grouping identifiermay be a grouping identifier. The intra-group buddy may be anassociation node. According to an embodiment of the present disclosure,a potential buddy list may be obtained, and the potential buddy of theuser may be obtained from the potential buddy list. There may be variousways for obtaining the potential buddy from the potential buddy list.For example, a matching weight of personal attribute information of theuser may be preconfigured, then personal attribute information of anon-buddy user and the personal attribute information of the user may becompared to obtain a weight of the non-buddy user, and a non-buddy userof which a weight is greater than a threshold may be regarded as thepotential buddy. The personal attribute information of the user mayinclude true information such as gender, age, constellation, a bloodtype, a graduate school, a major, a graduation date, a native place, alocation where the user locates, a job, hobbies, and so forth. When thesocial network is a virtual social network, the personal attributeinformation of the user may further include an area where the userlocates in the virtual world, attributes of a virtual character, a levelof the virtual character, and etc.

According to an embodiment of the present disclosure, the buddy groupingidentifier may include but not be limited to junior high schoolclassmate, senior high school classmate, college schoolmate, colleague,family, and etc. For example, a junior high school classmate user B in ajunior high school classmate group of user A may be an intra-group buddyof user A.

At step (b), a relevancy degree between the buddy and the user and arelevancy degree between the potential buddy and the user in each groupmay be obtained.

In this case, the potential buddy and the intra-group buddy may bepreconfigured as a node, and a condition for determining there is anassociation relationship between the node and an intra-group node may bepreconfigured. The condition may refer to the aforementioned conditionfor determining there is the association relationship between a node andan intra-group node in the grouping identifier, which is not repeatedherein.

At step (c), based on the relevancy degrees, the buddy and potentialbuddy in each group may be combined for outputting.

According to an embodiment of the present disclosure, the operations instep (c) may be implemented as follows.

At step (c1), the buddy and the potential buddy in each group may besorted according to the relevancy degrees.

At step (c2), the sorted buddy and potential buddy may be presentedbased on the buddy grouping identifier.

In this case, when each group is sorted, the sorted buddy and potentialbuddy may be presented based on the buddy grouping identifier. As shownin FIG. 5, there are three option controls on a display interface, whichmay display the buddy, or display the potential buddy, or display all ofthe users. A buddy list includes group 1 and group 2. Group 1 includesbuddy 1, potential buddy 1, buddy 2, potential buddy 2, buddy 3,potential buddy 34, and potential buddy 4. Group 2 includes buddy 4,buddy 5, potential buddy 5, and buddy 6.

Further, when the method for grouping the social network nodes isapplied to the grouping of buddies and potential buddies of the user,the method may include following operations after step (b).

At step (e), a relevancy threshold may be configured. A potential buddyof which a relevancy degree is less than the relevancy threshold may behidden.

In this case, the relevancy threshold may be configured by either theuser or the system according to requirements. When the relevancythreshold is preconfigured, it may be determined whether a relevancydegree of a potential buddy is less than the relevancy threshold. Inresponse to determining that the relevancy degree of the potential buddyis less than the relevancy threshold, the potential buddy may be hidden.In response to determining that the relevancy degree of the potentialbuddy is equal to or greater than the relevancy threshold, the potentialbuddy may be presented. In an embodiment, all of buddies of the user maybe presented to the user. In addition, the user may configure therelevancy threshold at any time according to the requirements. Forexample, a slider control may be configured on an interface, and therelevancy threshold may be adjusted through sliding the slider control.

According an embodiment of the present disclosure, when the method forgrouping the social network nodes is applied to the grouping of buddiesand potential buddies of the user, the method may further includefollowing operations.

At step (f), a display setting selected by the user may be obtained, andthe sorted buddy and potential buddy may be presented according to thedisplay setting and the buddy grouping identifier.

In this case, the display setting selected by the user may include anyone of presenting the buddy, presenting the potential buddy, andpresenting all of the users. The presenting may be performed accordingto a corresponding display setting. For example, referring to FIG. 5again, when the display setting is configured to present the buddy, thebuddies 1 to 6 may be presented. When the display setting is configuredto present the potential buddy, the potential buddies 1 to 5 may bepresented. When the display setting is configured to present all of theusers, all of the sorted buddies and potential buddies may be presented.

FIG. 6 is a schematic diagram illustrating a structure of an apparatusfor grouping social network nodes, according to an embodiment of thepresent disclosure. The apparatus may include an extracting module 10, aprocessing module 20, and an outputting module 30.

The extracting module 10 may obtain a candidate node having a potentialassociation relationship with a target node, an association node havingan association relationship with the target node, and a groupingidentifier of the association node.

In this case, a user in the social network may be selected as the targetnode. A user having a buddy relationship with the user may be regardedas the association node, i.e., a node having the associationrelationship with the target node may be regarded as the associationnode. A user having a potential buddy relationship with the user may beregarded as the candidate node, i.e., a node having the potentialassociation relationship with the target node may be regarded as thecandidate node. The candidate node having the potential associationrelationship with the target node may be obtained in advance. Thecandidate node may be placed in a candidate node list. A candidate nodeassociated with the target node may be obtained from the candidate nodelist. According to embodiments of the present disclosure, there may bevarious ways for obtaining the candidate node from the candidate nodelist. For example, a matching weight of attribute information of thetarget node may be preconfigured. Attribute information of nodes whichdo not have the association relationship with the target node may becompared with the attribute information of the target node, so as toobtain weights of the nodes which do not have the associationrelationship with the target node. When a weight of a node that does nothave the association relationship with the target node is greater than athreshold, the node may be regarded as the candidate node. The attributeinformation of a node may include true information such as gender, age,constellation, a blood type, a graduate school, a major, a graduationdate, a native place, a location where the node locates, a job, hobbies,and so forth. When the social network is a virtual social network, theattribute information of the node may further include an area where thenode locates in the virtual world, attributes of a virtual character, alevel of the virtual character, and etc.

According to an embodiment of the present disclosure, the groupingidentifier may include but not be limited to junior high schoolclassmate, senior high school classmate, college schoolmate, colleague,family, and etc. According to another embodiment of the presentdisclosure, the grouping identifier may be a group number (ID), such asgroup 001, group 002.

The processing module 20 may obtain a relevance degree between theassociation node and the target node and a relevance degree between thecandidate node and the target node within each grouping identifier.According to an embodiment of the present disclosure, the relevancedegree between the candidate node and the target node may be obtainedaccording to the grouping identifier, and the relevance degree betweenthe association node in each grouping identifier and the target node maybe obtained. The relevance degree may refer to a matching degree betweenthe attribute information of the target node and the attributeinformation of the candidate node, or between the attribute informationof the target node and the attribute information of the associationnode. According to an embodiment of the present disclosure, therelevance degree may be defined to mean a similarity degree of theattribute information between users.

According to an embodiment of the present disclosure, as shown in FIG.7, the processing module 20 may include an initialization sub-module210, a counting sub-module 220, and an obtaining sub-module 230 (whichis denoted as a calculating sub-module 230 in FIG. 7).

The initialization sub-module 210 may preconfigure a condition fordetermining there is the association relationship between a node and anintra-group node.

In this case, the target node, the association node, and the candidatenode may be regarded as the node. Association relationships between thenode and each intra-group node may be counted. According to anembodiment of the present disclosure, there may be two ways forobtaining the relevance degree of the node. According to a first way,when the intra-group nodes include the association nodes, the relevancedegree of the node may be obtained by counting the number of intra-groupassociation nodes having the association relationship with the node.According to a second way, when the intra-group nodes include theassociation nodes and the target node, the relevance degree of the nodemay be obtained by counting the number of the intra-group associationnodes plus the target node, in which the intra-group association nodeshave the association relationship with the node.

According to an embodiment of the present disclosure, the preconfiguredcondition for determining there is the association relationship betweenthe node and the intra-group node may include at least one of thefollowing conditions.

A first condition may be that the node itself is the intra-group node.

For example, when group 001 of target node A includes association nodeB, then association node B is an intra-group association node. Whenassociation node B is regarded as the node and the number of nodes ingroup 001 that may have the association relationship with associationnode B is counted, association node B itself may be counted.

A second condition may be that the node has the association relationshipwith the intra-group node.

For example, group 001 of target node A includes association node B,association node C, and association node D, in which association node Bhas the association relationship with association node C. Whenassociation node B is regarded as the node and the number of nodes ingroup 001 that may have the association relationship with associationnode B is counted, association node C meets the second condition and isregarded as a node in group 001 that has the association relationshipwith association node B.

A third condition may be that when the node has the associationrelationship with a predetermined number of candidate nodes and thepredetermined number of candidate nodes have the associationrelationship with the intra-group node, the node may have theassociation relationship with the intra-group node.

In this case, an intra-group association node may be a buddy of theuser, and a candidate node may likely to be a buddy of the user. Forexample, group 001 of target node A may include association node B,association node C, and association node D. Candidate nodes outside thegroup may include nodes E, F, G, and H. The predetermined number may bethree. Assuming candidate node E has the association relationship withcandidate nodes F, G and H, and association node B also has theassociation relationship with the candidate nodes F, G, and H, whencandidate node E is regarded as the node and the number of nodes ingroup 001 that may have the association relationship with candidate nodeE is counted, association node B meets the third condition and isregarded as a node in group 001 that has the association relationshipwith candidate node E.

The counting sub-module 220 may obtain, based on the condition, thenumber of intra-group nodes having the association relationship witheach node. For example, based on the condition, the number of nodes ingroup 001 that may have the association relationship with associationnode B may be counted, and the number of nodes in group 002 that mayhave the association relationship with association node B may becounted.

The obtaining sub-module 230 may configure a ratio of the number of theintra-group nodes having the association relationship with each node tothe number of the intra-group nodes as the relevance degree between eachnode and the target node, which may refer to FIG. 3 and not be repeatedherein.

According to an embodiment of the present disclosure, assuming theintra-group nodes include the association nodes and the target node,i.e., the target node may be regarded as a statistic node for obtainingthe relevance degree, as such, the nodes in the group G1 having theassociation relationship with A1 may include B1 (which meets the secondcondition), B3 (which meets the second condition), B6 (which meets thesecond condition and the third condition), and B5 (which meets the thirdcondition), so that the relevance degree of A1 may be 4/8. The nodes inthe group G1 having the association relationship with B5 may include B5(which meets the first condition), B1 (which meets the secondcondition), B2 (which meets the second condition), B4 (which meets thesecond condition), B7 (which meets the second condition), B6 (whichmeets the third condition), and the target node A, so that the relevancedegree of B5 may be 7/8.

The outputting module 30 may combine, based on the relevance degrees,the association node and candidate node in each grouping identifier andoutput the association node and candidate node.

According to an embodiment of the present disclosure, the outputtingmodule 30 may discretionarily combine the association node and thecandidate node in each group and output the association node and thecandidate node.

According to an embodiment of the present disclosure, as shown in FIG.8, the outputting module 30 may include a sorting sub-module 310 and apresenting sub-module 320.

The sorting sub-module 310 may sort, based on the relevancy degrees, theassociation node and the candidate node in each grouping identifier.Specifically, in each grouping identifier, the association node and thecandidate node in the grouping identifier may be sorted based on therelevance degrees. As shown in FIG. 3, in the grouping identifier G1,the relevance degrees of A1, A2, A3, and A4 respectively are 4/7, 2/7,2/7, and 2/7, and the relevance degrees of B1, B2, B3, B4, B5, B6, andB7 respectively are 5/7, 5/7, 4/7, 4/7, 6/7, 6/7, and 3/7. When thesenodes are sorted in a descending order of the relevance degrees, thenodes may be presented as B5, B6, B1, B2, B3, B4, A1, B7, A2, A3, andA4. According to another embodiment of the present disclosure, the nodesmay be sorted in an ascending order of the relevancy degrees.

The presenting sub-module 320 may present the sorted association nodeand candidate node according to the grouping identifier.

In this case, after each group is sorted, the sorted association nodeand candidate node may be presented according to the groupingidentifier. As shown in FIG. 4, there are three option controls on adisplay interface, which may display the association node, or displaythe candidate node, or display all of the nodes. An association nodelist includes group 1 and group 2. Group 1 includes association node 1,candidate node 1, association node 2, candidate node 2, association node3, candidate node 3, and candidate node 4. Group 2 includes associationnode 4, association node 5, candidate node 5, and association node 6.

According to an embodiment of the present disclosure, when theassociation node and the candidate node are presented, the associationnode and the candidate node may be marked with different labels fordistinguishing purpose. As shown in FIG. 4, a solid-line smiley may bemarked before an association node and a dotted-line smiley may be markedbefore a candidate node. According to embodiments of the presentdisclosure, the label may be configured by either the user or thesystem.

According to an embodiment of the present disclosure, when the relevancydegree of the candidate node in the grouping identifier is 0, thecandidate node may be hidden in the grouping identifier, alternatively,the candidate node may not be added to the grouping identifier. Forexample, when group 001 is processed, a relevancy degree betweencandidate node H and the target node is 0, so that candidate node H maynot be added to group 001. When group 002 is processed, the relevancydegree between candidate node H and the target node is not equal to 0,so that candidate node H may be added to group 002.

According to another embodiment of the present disclosure, the sortingsub-module 310 may sort the association node and the candidate node ineach group in a descending order of the relevancy degrees. Thepresenting sub-module 320 may present, within each grouping identifier,a predetermined number or a user-determined number of sorting resultswith high relevancy degrees. For example, referring to FIG. 3 again, ingroup G1, the relevance degrees of A1, A2, A3, and A4 respectively are4/7, 2/7, 2/7, and 2/7, and the relevance degrees of B1, B2, B3, B4, B5,B6, and B7 respectively are 5/7, 5/7, 4/7, 4/7, 6/7, 6/7, and 3/7. Whenthese nodes are sorted in the descending order of the relevance degrees,the nodes may be presented as B5, B6, B1, B2, B3, B4, A1, B7, A2, A3,and A4. When the predetermined number is 7, B5, B6, B1, B2, B3, B4, andA1 may be presented. When the user-determined number is 6, B5, B6, B1,B2, B3, and B4 may be presented.

As shown in FIG. 9, in addition to the extracting module 10, theprocessing module 20, and the outputting module 30, the apparatus forgrouping the social network nodes may further include a preconfiguringmodule 40, a determining module 50, a hiding module 60, and an inputtingmodule 70.

The preconfiguring module 40 may configure a relevancy threshold.According to an embodiment of the present disclosure, the relevancythreshold may be configured by either the user or the system accordingto requirements.

The determining module 50 may determine whether a relevancy degree of acandidate node is less than the relevancy threshold.

The hiding module 60 may hide the candidate node in response todetermining that the relevancy degree of the candidate node is less thanthe relevancy threshold.

The sorting sub-module 310 may sort, within each group in which thecandidate node of which the relevancy degree is less than the relevancythreshold is hidden, the association node and the candidate node basedon the relevancy degrees.

The presenting sub-module 320 may present the association node and thecandidate node sorted based on the relevancy degrees within each groupin which the candidate node of which the relevancy degree is less thanthe relevancy threshold is hidden.

The inputting module 70 may obtain a display setting selected by theuser. Specifically, the display setting selected by the user may includeany one of presenting the association node, presenting the candidatenode, and presenting all of the nodes. The presenting may be performedaccording to a corresponding display setting. For example, referring toFIG. 3 again, when the display setting is configured to present theassociation node, the association nodes B1 to B7 may be presented. Whenthe display setting is configured to present the candidate node, thecandidate nodes A1 to A4 may be presented. When the display setting isconfigured to present all of the nodes, all of the sorted associationnode and candidate node may be presented.

The presenting sub-module 320 may present the sorted association nodeand candidate node according to the display setting and the groupingidentifier.

According to another embodiment of the present disclosure, in theapparatus for grouping the social network nodes, the sorting sub-module310 may sort, within each group in which the candidate node of which therelevancy degree is less than the relevancy threshold is hidden, theassociation node and the candidate node in the descending order of therelevancy degrees. The presenting sub-module 320 may present apredetermined number or a user-determined number of sorting results withhigh relevancy degrees within each grouping identifier.

When the apparatus for grouping the social network nodes is applied tothe grouping of buddies and potential buddies of the user, correspondingprocedures may refer to the operations in the aforementioned method, inwhich a corresponding step may be implemented by a corresponding module,which are not repeated herein.

According to various embodiments of the present disclosure, in themethod and apparatus for grouping the social network nodes as describedabove, the candidate node having the potential association relationshipwith the target node, the association node having the associationrelationship with the target node, and the grouping identifier of theassociation node can be obtained. The relevance degree of the candidatenode and the relevance degree of the association node within eachgrouping identifier can be obtained. Based on the relevance degrees, theassociation node and the candidate node in each grouping identifier canbe combined for outputting. The method and apparatus described in thevarious embodiments of the present disclosure can facilitate theoperation, reduce the operations implemented by the user for adding thecandidate node, and improve the response efficiency of the system.

In addition, the relevant threshold is configured and part of candidatenodes can be hidden, so that the presenting space can be saved. Further,the association nodes and the candidate nodes can be presented accordingto the display setting selected by the user, and therefore thepresenting is flexible.

Those skilled in the art may understand that all or part of theprocedures of the methods of the above embodiments may be implemented byhardware modules following computer readable instructions. The computerreadable instructions may be stored in a computer-readable storagemedium. When running, the computer readable instructions may provide theprocedures of the method embodiments as described above. The storagemedium may be diskette, CD, ROM (Read-Only Memory) or RAM (Random AccessMemory), and etc.

What has been described and illustrated herein is an embodiment of thedisclosure along with some of its variations. The terms, descriptionsand figures used herein are set forth by way of illustration only andare not meant as limitations. Many variations are possible within thespirit and scope of the disclosure, which is intended to be defined bythe following claims—and their equivalents—in which all terms are meantin their broadest reasonable sense unless otherwise indicated.

The invention claimed is:
 1. A method for recommending friends to a userof a social networking group, performed by a computing device,comprising: obtaining user identifiers of members of the socialnetworking group; dividing the members of the social networking groupinto a first set of members that have a direct relationship with theuser and a second set of members that have no direct relationship withthe user; for each of the user identifiers of the social networkinggroup: determining a total number of members within the first set ofmembers whose relationship with a corresponding member satisfy at leastone of a set of predefined conditions including: the correspondingmember being a member of the first set of members; the correspondingmember having the direct relationship with a member of the first set ofmembers; and when the corresponding member has the direct relationshipwith a predetermined number of members of the second set of members andthe predetermined number of members of the second set of members havethe direct relationship with a member of the first set of members, thecorresponding member having the relationship with a member of the firstset of members; dividing the total number of members within the firstset of members whose relationship with the corresponding member satisfyat least one of the set of predefined conditions by a total number ofmembers within the first set of members as a relevance degree betweenthe corresponding member and the other members of the social networkinggroup; displaying the user identifiers of the members in the socialnetworking group according to their respective calculated relevancedegrees, wherein at least one member in the second set of members has arelevance degree higher than that of at least one member in the firstset of members; receiving a user selection of the user identifier of theat least one member in the second set of members; and establishing adirect relationship between the user and the at least one member in thesecond set of members.
 2. The method of claim 1, wherein the operationof displaying the user identifiers of the members in the socialnetworking group comprises: sorting the user identifiers of the membersin the social networking group based on their respective calculatedrelevancy degrees; and displaying the sorted user identifiers of themembers in the social networking group.
 3. The method of claim 2,wherein before the operation of sorting, the method further comprises:hiding based on a preconfigured relevancy threshold, a user identifierof a member in the second set of members of which a relevancy degree isless than the relevancy threshold; wherein the operation of sorting theuser identifiers of the members in the social networking groupcomprises: after the hiding the user identifier of the member in thesecond set of members of which the relevancy degree is less than therelevancy threshold, sorting remaining user identifiers of the membersin the social networking group based on their respective calculatedrelevancy degrees.
 4. The method of claim 2, wherein the operation ofsorting comprises: sorting the user identifiers of the members in thesocial networking group in a descending order of the relevancy degrees;wherein the operation of displaying comprises: displaying apredetermined number or a user-determined number of sorting results withhigh relevancy degrees.
 5. The method of claim 2, further comprising:obtaining a display setting selected by a user; and displaying thesorted user identifiers of the members in the social networking groupaccording to the display setting.
 6. An apparatus for recommendingfriends to a user of a social networking group, comprising: a processorand a memory which stores computer-readable instructions being executedby the processor to: obtain user identifiers of members of the socialnetworking group; divide the members of the social networking group intoa first set of members that have a direct relationship with the user anda second set of members that have no direct relationship with the user;for each of the user identifiers of the social networking group:determine a total number of members within the first set of memberswhose relationship with a corresponding member satisfy at least one of aset of predefined conditions including: the corresponding member being amember of the first set of members; the corresponding member having thedirect relationship with a member of the first set of members; and whenthe corresponding member has the direct relationship with apredetermined number of members of the second set of members and thepredetermined number of members of the second set of members have thedirect relationship with a member of the first set of members, thecorresponding member having the relationship with a member of the firstset of members; divide the total number of members within the first setof members whose relationship with the corresponding member satisfy atleast one of the set of predefined conditions by a total number ofmembers within the first set of members as a relevance degree betweenthe corresponding member and the other members of the social networkinggroup; and display the user identifiers of the members in the socialnetworking group according to their respective calculated relevancedegrees, wherein at least one member in the second set of members has arelevance degree higher than that of at least one member in the firstset of members; receive a user selection of the user identifier of theat least one member in the second set of members; and establish a directrelationship between the user and the at least one member in the secondset of members.
 7. The apparatus of claim 6, wherein the instructionsare executable by the processor to: sort the user identifiers of themembers in the social networking group based on their respectivecalculated relevancy degrees; and display the sorted user identifiers ofthe members in the social networking group.
 8. The apparatus of claim 7,wherein the instructions are executable by the processor to:preconfigure a relevancy threshold; determine whether a relevancy degreeof a member in the second set of members is less than the relevancythreshold; and hide a user identifier of the member in the second set ofmembers of which the relevancy degree is less than the relevancythreshold; after hiding the user identifier of the member in the secondset of members of which the relevancy degree is less than the relevancythreshold, sort remaining user identifiers of the members in the socialnetworking group based on their respective calculated relevancy degrees.9. The apparatus of claim 7, wherein the instructions are executable bythe processor to sort user identifiers of the members in the socialnetworking group in a descending order of the relevancy degrees; anddisplay a predetermined number or a user-determined number of sortingresults with high relevancy degrees.
 10. The apparatus of claim 7,wherein the instructions are executable by the processor to: obtain adisplay setting selected by a user; display the sorted user identifiersof the members in the social networking group according to the displaysetting.
 11. A non-transitory computer-readable storage medium encodedwith a plurality of instructions that when executed by one or morecomputers cause the one or more computers to perform operations forrecommending friends to a user of a social networking group, theoperations comprising: obtaining user identifiers of members of thesocial networking group; dividing the members of the social networkinggroup into a first set of members that have a direct relationship withthe user and a second set of members that have no direct relationshipwith the user; for each of the user identifiers of the social networkinggroup: determining a total number of members within the first set ofmembers whose relationship with a corresponding member satisfy at leastone of a set of predefined conditions including: the correspondingmember being a member of the first set of members; the correspondingmember having the direct relationship with a member of the first set ofmembers; and when the corresponding member has the direct relationshipwith a predetermined number of members of the second set of members andthe predetermined number of members of the second set of members havethe direct relationship with a member of the first set of members, thecorresponding member having the relationship with a member of the firstset of members; dividing the total number of members within the firstset of members whose relationship with the corresponding member satisfyat least one of the set of predefined conditions by a total number ofmembers within the first set of members as a relevance degree betweenthe corresponding member and the other members of the social networkinggroup; displaying the user identifiers of the members in the socialnetworking group according to their respective calculated relevancedegrees, wherein at least one member in the second set of members has arelevance degree higher than that of at least one member in the firstset of members; receiving a user selection of the user identifier of theat least one member in the second set of members; and establishing adirect relationship between the user and the at least one member in thesecond set of members.
 12. The non-transitory computer-readable storagemedium of claim 11, wherein the operation of displaying the useridentifiers of the members in the social networking group comprises:sorting the user identifiers of the members in the social networkinggroup based on their respective calculated relevancy degrees; anddisplaying the sorted user identifiers of the members in the socialnetworking group.
 13. The non-transitory computer-readable storagemedium of claim 12, before the operation of sorting, further comprisinginstructions that cause the one or more computers to perform operationscomprising: hiding, based on a preconfigured relevancy threshold, a useridentifier of a member in the second set of members of which a relevancydegree is less than the relevancy threshold; wherein the operation ofsorting the user identifiers of the members in the social networkinggroup comprises: after the hiding the user identifier of the member inthe second set of members of which the relevancy degree is less than therelevancy threshold, sorting remaining user identifiers of the membersin the social networking group based on their respective calculatedrelevancy degrees.
 14. The non-transitory computer-readable storagemedium of claim 13, wherein the operation of sorting comprises: sortingthe user identifiers of the members in the social networking group in adescending order of the relevancy degrees; wherein the operation ofdisplaying comprises: displaying a predetermined number or auser-determined number of sorting results with high relevancy degrees.15. The non-transitory computer-readable storage medium of claim 13,further comprising instructions that cause the one or more computers toperform operations comprising: obtaining a display setting selected by auser; and displaying the sorted user identifiers of the members in thesocial networking group according to the display setting.